Changing times: trends in risk classification, tumor upstaging, and positive surgical margins after radical prostatectomy - results from a contemporary National Cancer Database study.

PURPOSE: Recent advancements in screening, prostate MRI, robotic surgery, and active surveillance have influenced the profile of patients undergoing radical prostatectomy (RP). We sought to examine their impact on trends in clinicodemographic, risk classification, and adverse pathology in men undergoing surgery. METHODS: We queried the National Cancer Database for clinicodemographic, risk group, and pathology data in men undergoing upfront RP between 2006 and 2020. Patients were categorized by NCCN risk groups, and trends were assessed among 2006-2010, 2011-2015, and 2016-2020 periods. Endpoints included rates of pT3, positive surgical margins (PSM), pathologic upstaging, and Gleason grade group (GG) upgrading. RESULTS: 610,762 patients were included. There were significant increases in African Americans (9.8-14.1%), comorbidities (2.1-5.2% with Charlson scores > 1), and robot-assisted RP (78-84%). Over the three time periods, high-risk cases increased from 15 to 20 to 27%, and intermediate-risk from 54 to 51 to 60%. Overall rates of pT3 rose from 20 to 38%, and PSM from 20 to 27% (p < 0.001). Pathologic upstaging increased in low (6-15%), intermediate (20-33%), and high-risk groups (42-58%) -p < 0.001. Gleason upgrading rose in low-risk (45-59%, p < 0.001), with slight reductions in the intermediate and high-risk groups. CONCLUSIONS: Recent trends in RP indicate a shift towards more advanced disease, evidenced by increasing rates of pT3, PSM, and pathologic upstaging across all NCCN risk groups. These findings emphasize the need for a careful balance in applying fascia and nerve-sparing techniques to avoid compromising oncological safety.

Predicting the Risk of Maxillary Canine Impaction Based on Maxillary Measurements Using Supervised Machine Learning.

OBJECTIVES: To predict palatally impacted maxillary canines based on maxilla measurements through supervised machine learning techniques. MATERIALS AND METHODS: The maxilla images from 138 patients were analysed to investigate intermolar width, interpremolar width, interpterygoid width, maxillary length, maxillary width, nasal cavity width and nostril width, obtained through cone beam computed tomography scans. The predictive models were built using the following machine learning algorithms: Adaboost Classifier, Decision Tree, Gradient Boosting Classifier, K-Nearest Neighbours (KNN), Logistic Regression, Multilayer Perceptron Classifier (MLP), Random Forest Classifier and Support Vector Machine (SVM). A 5-fold cross-validation approach was employed to validate each model. Metrics such as area under the curve (AUC), accuracy, recall, precision and F1 Score were calculated for each model, and ROC curves were constructed. RESULTS: The predictive model included four variables (two dental and two skeletal measurements). The interpterygoid width and nostril width showed the largest effect sizes. The Gradient Boosting Classifier algorithm exhibited the best metrics, with AUC values ranging from 0.91 [CI95% = 0.74-0.98] for test data to 0.89 [CI95% = 0.86-0.94] for crossvalidation. The nostril width variable demonstrated the highest importance across all tested algorithms. CONCLUSION: The use of maxillary measurements, through supervised machine learning techniques, is a promising method for predicting palatally impacted maxillary canines. Among the models evaluated, both the Gradient Boosting Classifier and the Random Forest Classifier demonstrated the best performance metrics, with accuracy and AUC values exceeding 0.8, indicating strong predictive capability.

Anti-Inflammatory Activity and Acute Toxicity Of Pereskia aculeata, In Zophobas morio Larvae.

Pereskia aculeata has been widely investigated due to its anti-inflammatory potential. Among the metabolites found in this species are the phytosterols beta-sitosterol (ß-SIT) and stigmasterol (STIG). The objective of the study was to evaluate the anti-inflammatory and toxicity activities of the hexane partition of P. aculeata (PHEX), as well as ß-SIT and STIG. PHEX was prepared and the phytosterols were quantified. In terms of toxicity against L929 fibroblast cells, PHEX showed toxicity up to 200 µg/mL; STIG and ß-SIT showed toxicity up to 25 µg/mL. PHEX inhibited 66 % of nitric oxide radicals, while STIG and ß-SIT inhibited 33.73 % and 34.94 %, respectively. In an anti-inflammatory test against Zophobas morio larvae, all samples significantly reduced hemocyte levels. Additionally, the LD50 values were calculated: 229.6 mg/kg for PHEX, 101.5 mg/kg for STIG, and 103.8 mg/kg for ß-SIT. In conclusion, the study indicates that the phytosterols present in PHEX may contribute to its anti-inflammatory activity.

Genomic predictions and GWAS for heat tolerance in pigs based on reaction norm models with performance records and data from public weather stations considering alternative temperature thresholds.

Genetic improvement of livestock productivity has resulted in greater production of metabolic heat and potentially greater susceptibility to heat stress. Various studies have demonstrated that there is genetic variability for heat tolerance and genetic selection for more heat tolerant individuals is possible. The rate of genetic progress tends to be greater when genomic information is incorporated into the analyses as more accurate breeding values can be obtained for young individuals. Therefore, this study aimed (1) to evaluate the predictive ability of genomic breeding values for heat tolerance based on routinely recorded traits, and (2) to investigate the genetic background of heat tolerance based on single-step genome-wide association studies for economically important traits related to body composition, growth and reproduction in Large White pigs. Pedigree information was available for 265,943 animals and genotypes for 8686 animals. The studied traits included ultrasound backfat thickness (BFT), ultrasound muscle depth (MDP), piglet weaning weight (WW), off-test weight (OTW), interval between farrowing (IBF), total number of piglets born (TNB), number of piglets born alive (NBA), number of piglets born dead (NBD), number of piglets weaned (WN) and weaning-to-estrus interval (IWE). The number of phenotypic records ranged from 6059 (WN) to 172,984 (TNB). Single-step genomic reaction norm predictions were used to calculate the genomic estimated breeding values for each individual. Predictions of breeding values for the validation population individuals were compared between datasets containing phenotypic records measured in the whole range of temperatures (WR) and datasets containing only phenotypic records measured when the weather station temperature was above 10°C (10C) or 15°C (15C), to evaluate the usefulness of these datasets that may better reflect the within-barn temperature. The use of homogeneous or heterogeneous residual variance was found to be trait-dependent, where homogeneous variance presented the best fit for MDP, BFT, OTW, TNB, NBA, WN and IBF, while the other traits (WW and IWE) had better fit with heterogeneous variance. The average prediction accuracy, dispersion and bias values considering all traits for WR were 0.36 ± 0.05, -0.07 ± 0.13 and 0.76 ± 0.10, respectively; for 10C were 0.39 ± 0.02, -0.05 ± 0.07 and 0.81 ± 0.05, respectively; and for 15C were 0.32 ± 0.05, -0.05 ± 0.11 and 0.84 ± 0.10, respectively. Based on the studied traits, using phenotypic records collected when the outside temperature (from public weather stations) was above 10°C provided better predictions for most of the traits. Forty-three and 62 candidate genomic regions were associated with the intercept (overall performance level) and slope term (specific biological mechanisms related to environmental sensitivity), respectively. Our results contribute to improve genomic predictions using existing datasets and better understand the genetic background of heat tolerance in pigs. Furthermore, the genomic regions and candidate genes identified will contribute to future genomic studies and breeding applications.

Obtaining Cellulose Fibers from Almond Shell by Combining Subcritical Water Extraction and Bleaching with Hydrogen Peroxide.

Almond shell (AS) represents about 33% of the almond fruit, being a cellulose-rich by-product. The use of greener methods for separating cellulose would contribute to better exploitation of this biomass. Subcritical water extraction (SWE) at 160 and 180 °C has been used as a previous treatment to purify cellulose of AS, followed by a bleaching step with hydrogen peroxide (8%) at pH 12. For comparison purposes, bleaching with sodium chlorite of the extraction residues was also studied. The highest extraction temperature promoted the removal of hemicellulose and the subsequent delignification during the bleaching step. After bleaching with hydrogen peroxide, the AS particles had a cellulose content of 71 and 78%, with crystallinity index of 50 and 62%, respectively, for those treated at 160 and 180 °C. The use of sodium chlorite as bleaching agent improved the cellulose purification and crystallinity index. Nevertheless, cellulose obtained by both bleaching treatments could be useful for different applications. Therefore, SWE represents a promising green technique to improve the bleaching sensitivity of lignocellulosic residues, such as AS, allowing for a great reduction in chemicals in the cellulose purification processes.

The Genetic Landscape and Epidemiology of Phenylketonuria.

Phenylketonuria (PKU), caused by variants in the phenylalanine hydroxylase (PAH) gene, is the most common autosomal-recessive Mendelian phenotype of amino acid metabolism. We estimated that globally 0.45 million individuals have PKU, with global prevalence 1:23,930 live births (range 1:4,500 [Italy]-1:125,000 [Japan]). Comparing genotypes and metabolic phenotypes from 16,092 affected subjects revealed differences in disease severity in 51 countries from 17 world regions, with the global phenotype distribution of 62% classic PKU, 22% mild PKU, and 16% mild hyperphenylalaninemia. A gradient in genotype and phenotype distribution exists across Europe, from classic PKU in the east to mild PKU in the southwest and mild hyperphenylalaninemia in the south. The c.1241A>G (p.Tyr414Cys)-associated genotype can be traced from Northern to Western Europe, from Sweden via Norway, to Denmark, to the Netherlands. The frequency of classic PKU increases from Europe (56%) via Middle East (71%) to Australia (80%). Of 758 PAH variants, c.1222C>T (p.Arg408Trp) (22.2%), c.1066-11G>A (IVS10-11G>A) (6.4%), and c.782G>A (p.Arg261Gln) (5.5%) were most common and responsible for two prevalent genotypes: p.[Arg408Trp];[Arg408Trp] (11.4%) and c.[1066-11G>A];[1066-11G>A] (2.6%). Most genotypes (73%) were compound heterozygous, 27% were homozygous, and 55% of 3,659 different genotypes occurred in only a single individual. PAH variants were scored using an allelic phenotype value and correlated with pre-treatment blood phenylalanine concentrations (n = 6,115) and tetrahydrobiopterin loading test results (n = 4,381), enabling prediction of both a genotype-based phenotype (88%) and tetrahydrobiopterin responsiveness (83%). This study shows that large genotype databases enable accurate phenotype prediction, allowing appropriate targeting of therapies to optimize clinical outcome.

Can numerical rating scales of disease impact be used as targets for patient-centred management in rheumatoid arthritis?

OBJECTIVES: Patient centred care is an increasingly important paradigm. Applying a treat-to-target strategy to the impact of the disease in patients' lives seems a very promising tool to serve this purpose. We aimed to evaluate if maximum acceptable impact scores (target-values) defined at the population level provide an appropriate representation for most individual patients. To determine if the individually established target values of impact are consistent enough to be used in a treat-to-target strategy. METHODS: Consecutive patients with rheumatoid arthritis were asked to indicate, in two consecutive visits, the maximum severity of impact they considered acceptable to live with for the rest of their lives, in the seven domains of Rheumatoid Arthritis Impact of Disease score. The individual adequacy of population-based reference values was assessed by measures of dispersion. Stability of individual target-values were evaluated through intraclass correlation coefficient. Socio-demographic, clinical and psychological features were tested as co-factors of stability. RESULTS: 299 patients were included. The dispersion of targets was wide (CV>0.68), thus limiting the use of any population-based single values as targets for the individual patients. Although the mean target values were very similar in both visits for all domains, reliability was poor in all cases (ICCs: 0.37-0.47). Only 25-30% of the patients selected the same target value in the 2 visits. No explanatory factors for (non-)stability were identified. CONCLUSIONS: Quantified impact targets defined at population level are not appropriate for individual patient care. Research on alternative tools to support patient-centred, target-oriented management strategies is warranted.

Genetic parameters for automatically-measured vaginal temperature, respiration efficiency, and other thermotolerance indicators measured on lactating sows under heat stress conditions.

BACKGROUND: Genetic selection based on direct indicators of heat stress could capture additional mechanisms that are involved in heat stress response and enable more accurate selection for more heat-tolerant individuals. Therefore, the main objectives of this study were to estimate genetic parameters for various heat stress indicators in a commercial population of Landrace × Large White lactating sows measured under heat stress conditions. The main indicators evaluated were: skin surface temperatures (SST), automatically-recorded vaginal temperature (TV), respiration rate (RR), panting score (PS), body condition score (BCS), hair density (HD), body size (BS), ear size, and respiration efficiency (Reff). RESULTS: Traits based on TV presented moderate heritability estimates, ranging from 0.15 ± 0.02 to 0.29 ± 0.05. Low heritability estimates were found for SST traits (from 0.04 ± 0.01 to 0.06 ± 0.01), RR (0.06 ± 0.01), PS (0.05 0.01), and Reff (0.03 ± 0.01). Moderate to high heritability values were estimated for BCS (0.29 ± 0.04 for caliper measurements and 0.25 ± 0.04 for visual assessments), HD (0.25 ± 0.05), BS (0.33 ± 0.05), ear area (EA; 0.40 ± 0.09), and ear length (EL; 0.32 ± 0.07). High genetic correlations were estimated among SST traits (> 0.78) and among TV traits (> 0.75). Similarly, high genetic correlations were also estimated for RR with PS (0.87 ± 0.02), with BCS measures (0.92 ± 0.04), and with ear measures (0.95 ± 0.03). Low to moderate positive genetic correlations were estimated between SST and TV (from 0.25 ± 0.04 to 0.76 ± 0.07). Low genetic correlations were estimated between TV and BCS (from - 0.01 ± 0.08 to 0.06 ± 0.07). Respiration efficiency was estimated to be positively and moderately correlated with RR (0.36 ± 0.04), PS (0.56 ± 0.03), and BCS (0.56 ± 0.05 for caliper measurements and 0.50 ± 0.05 for the visual assessments). All other trait combinations were lowly genetically correlated. CONCLUSIONS: A comprehensive landscape of heritabilities and genetic correlations for various thermotolerance indicators in lactating sows were estimated. All traits evaluated are under genetic control and heritable, with different magnitudes, indicating that genetic progress is possible for all of them. The genetic correlation estimates provide evidence for the complex relationships between these traits and confirm the importance of a sub-index of thermotolerance traits to improve heat tolerance in pigs.

Longitudinal genomic analyses of automatically-recorded vaginal temperature in lactating sows under heat stress conditions based on random regression models.

BACKGROUND: Automatic and continuous recording of vaginal temperature (TV) using wearable sensors causes minimal disruptions to animal behavior and can generate data that enable the evaluation of temporal body temperature variation under heat stress (HS) conditions. However, the genetic basis of TV in lactating sows from a longitudinal perspective is still unknown. The objectives of this study were to define statistical models and estimate genetic parameters for TV in lactating sows using random regression models, and identify genomic regions and candidate genes associated with HS indicators derived from automatically-recorded TV. RESULTS: Heritability estimates for TV ranged from 0.14 to 0.20 over time (throughout the day and measurement period) and from 0.09 to 0.18 along environmental gradients (EG, - 3.5 to 2.2, which correspond to dew point values from 14.87 to 28.19 ËšC). Repeatability estimates of TV over time and along EG ranged from 0.57 to 0.66 and from 0.54 to 0.77, respectively. TV measured from 12h00 to 16h00 had moderately high estimates of heritability (0.20) and repeatability (0.64), indicating that this period might be the most suitable for recording TV for genetic selection purposes. Significant genotype-by-environment interactions (GxE) were observed and the moderately high estimates of genetic correlations between pairs of extreme EG indicate potential re-ranking of selection candidates across EG. Two important genomic regions on chromosomes 10 (59.370-59.998 Mb) and16 (21.548-21.966 Mb) were identified. These regions harbor the genes CDC123, CAMK1d, SEC61A2, and NUDT5 that are associated with immunity, protein transport, and energy metabolism. Across the four time-periods, respectively 12, 13, 16, and 10 associated genomic regions across 14 chromosomes were identified for TV. For the three EG classes, respectively 18, 15, and 14 associated genomic windows were identified for TV, respectively. Each time-period and EG class had uniquely enriched genes with identified specific biological functions, including regulation of the nervous system, metabolism and hormone production. CONCLUSIONS: TV is a heritable trait with substantial additive genetic variation and represents a promising indicator trait to select pigs for improved heat tolerance. Moderate GxE for TV exist, indicating potential re-ranking of selection candidates across EG. TV is a highly polygenic trait regulated by a complex interplay of physiological, cellular and behavioral mechanisms.

Peak left atrial longitudinal strain is associated with all-cause mortality in patients with ventricular functional mitral regurgitation.

PURPOSE: Chronic mitral regurgitation promotes left atrial (LA) remodeling. However, the significance of LA dysfunction in the setting of ventricular functional mitral regurgitation (FMR) has not been fully investigated. Our aim was to assess the prognostic impact of peak atrial longitudinal strain (PALS), a surrogate of LA function, in patients with FMR and reduced left ventricular ejection fraction (LVEF). METHODS: Patients with at least mild ventricular FMR and LVEF < 50% under optimized medical therapy who underwent transthoracic echocardiography at a single center were retrospectively identified in the laboratory database. PALS was assessed by 2D speckle tracking in the apical 4-chamber view and the study population was divided in two groups according to the best cut-off value of PALS, using receiver operating characteristics (ROC) curve analysis. The primary endpoint-point was all-cause mortality. RESULTS: A total of 307 patients (median age 70 years, 77% male) were included. Median LVEF was 35% (IQR: 27 - 40%) and median effective regurgitant orifice area (EROA) was 15mm2 (IQR: 9 - 22mm2). According to current European guidelines, 32 patients had severe FMR (10%). During a median follow-up of 3.5 years (IQR 1.4 - 6.6), 148 patients died. The unadjusted mortality incidence per 100 persons-years increased with progressively lower values of PALS. On multivariable analysis, PALS remained independently associated with all-cause mortality (adjusted hazard ratio 1.052 per % decrease; 95% CI: 1.010 - 1.095; P = 0.016), even after adjustment for several (n = 14) clinical and echocardiographic confounders. CONCLUSION: PALS is independently associated with all-cause mortality in patients with reduced LVEF and ventricular FMR.

Effect of postoperative tranexamic acid on recurrence rate and complications in chronic subdural hematomas patients: preliminary results of a randomized controlled clinical trial.

Chronic subdural hematoma (CSDH) is a frequent neurosurgical disease which mainly affects elderly patients. Tranexamic acid (TXA) has been hypothesized as an oral agent to avoid CSDH progression and/or recurrence. We performed an evaluation to determine whether the postoperative use of TXA reduces recurrence rate. A prospective, randomized, and controlled trial. Patients with unilateral or bilateral chronic subdural hematoma undergoing surgical treatment by burr-hole were randomized as to whether or not to use TXA in the postoperative period. We evaluated image and clinical recurrence of CSDH at follow up of 6 months and potential clinical and/or surgical complications impact of TXA. Twenty-six patients were randomized to the control group (52%) and twenty-four patients to the TXA group (48%). Follow-up ranged from 3 to 16 months. There were no significant difference between baseline data in groups regarding to age, gender, use of antiplatelet or anticoagulants, smoking, alcoholism, systemic arterial hypertension, diabetes mellitus, hematoma laterality, hematoma thickness, and drain use. Clinical and radiological recurrence occurred in three patients (6%), being two cases in TXA group (8.3%) and 1 in control group (3.8%). Postoperative complications occurred in two patients during follow-up (4%), being both cases in TXA group (8.3%), and none in the control group. Although TXA group had a higher recurrence rate (8.3%), there was no statistically significant difference between the two groups. Moreover, TXA group had two complications while control group had no complications. Although limited by experimental nature of study and small sample, our current data suggest that TXA should not be used as a potential agent to avoid recurrences of CSDH and might increase complication odds.

Multicenter retrospective study on benign testicular tumors in children: save as much as you can please.

BACKGROUND: Testicular tumors (TT) are infrequent in pediatric patients, representing 1% of pediatric solid tumors; benign testicular tumors (BTT) are the most common. We present a multicenter study aiming to describe the incidence, histology and surgical technique of BTT, with special emphasis on which approach could present better outcomes. METHODS: The records of pediatric patients diagnosed with BTT between 2005 and 2020 from 8 centers in 5 different countries in Latin-America, were reviewed. RESULTS: Sixty two BTTs were identified. 73% tumors presented as a testicular mass, and 97% underwent testicular ultrasound as the initial imaging study, all of them had findings suggestive of a benign tumor. 87% had preoperative tumor markers (AFP and BHCG). In 66%, an intraoperative biopsy was done and 98% of the intraoperative biopsies were concordant with the final pathology report. Tumorectomy was performed in 81% of patients and total orchiectomy in the remaining 19%. Six percentage of patients underwent a subsequent orchiectomy. Mean follow-up was 39 months (1-278 months) where no cases of atrophy were observed clinically or on ultrasound. Fertility was not evaluated in this series. CONCLUSIONS: Proper management of BTTs is essential to avoid unnecessary orchiectomies. Preoperative ultrasound associated with intraoperative biopsy seems accurate in identifying benign pathology, thus enabling conservative testicular surgery with safety margins. Based on this multicenter series, we suggest performing an intraoperative biopsy with subsequent tumorectomy preserving healthy testicular tissue in BTT.

Single Modality vs. Multimodality: What Works Best for Lung Cancer Screening?

In a clinical context, physicians usually take into account information from more than one data modality when making decisions regarding cancer diagnosis and treatment planning. Artificial intelligence-based methods should mimic the clinical method and take into consideration different sources of data that allow a more comprehensive analysis of the patient and, as a consequence, a more accurate diagnosis. Lung cancer evaluation, in particular, can benefit from this approach since this pathology presents high mortality rates due to its late diagnosis. However, many related works make use of a single data source, namely imaging data. Therefore, this work aims to study the prediction of lung cancer when using more than one data modality. The National Lung Screening Trial dataset that contains data from different sources, specifically, computed tomography (CT) scans and clinical data, was used for the study, the development and comparison of single-modality and multimodality models, that may explore the predictive capability of these two types of data to their full potential. A ResNet18 network was trained to classify 3D CT nodule regions of interest (ROI), whereas a random forest algorithm was used to classify the clinical data, with the former achieving an area under the ROC curve (AUC) of 0.7897 and the latter 0.5241. Regarding the multimodality approaches, three strategies, based on intermediate and late fusion, were implemented to combine the information from the 3D CT nodule ROIs and the clinical data. From those, the best model-a fully connected layer that receives as input a combination of clinical data and deep imaging features, given by a ResNet18 inference model-presented an AUC of 0.8021. Lung cancer is a complex disease, characterized by a multitude of biological and physiological phenomena and influenced by multiple factors. It is thus imperative that the models are capable of responding to that need. The results obtained showed that the combination of different types may have the potential to produce more comprehensive analyses of the disease by the models.

Exercise Oscillatory Ventilation Improves Heart Failure Prognostic Scores.

BACKGROUND: Several heart failure (HF) prognostic risk scores are available to guide the ideal time for listing candidates for a heart transplant (HTx). The detection of exercise oscillatory ventilation (EOV) during cardiopulmonary exercise testing (CPET) is associated with advanced HF and a worse prognosis, and yet it is not accounted for in these risk scores. Therefore, this study aimed to assess whether EOV further adds prognostic value to HF scores. METHODS: A single-centre retrospective cohort study was undertaken of consecutive HF patients with reduced ejection fraction (HFrEF) who underwent CPET from 1996 to 2018. The Heart Failure Survival Score (HFSS), Seattle Heart Failure Model (SHFM), Meta-analysis Global Group In Chronic Heart Failure (MAGGIC), and Metabolic Exercise Cardiac Kidney Index (MECKI) were calculated. The added value of EOV on top of those scores was assessed using a Cox proportional hazard model. The added discriminative power was also assessed by receiver operating characteristic curve comparison. RESULTS: A total of 390 HF patients with a median age of 58 (IQR 50-65) years were investigated, of whom 78% were male and 54% had ischaemic heart disease. The median peak oxygen consumption was 15.7 mL/kg/min (IQR 12.8-20.1). Exercise oscillatory ventilation was detected in 153 (39.2%) patients. Over a median follow-up of 2 years, 61 patients died (49 due to a cardiovascular reason) and 54 had a HTx. Exercise oscillatory ventilation independently predicted the composite outcome of all-cause death and HTx. Furthermore, the presence of this ventilatory pattern significantly improved the prognostic performance of both HFSS and MAGGIC scores. CONCLUSION: Exercise oscillatory ventilation was often found in a cohort of HF patients with reduced LVEF who underwent CPET. It was found that EOV added further prognostic value to contemporary HF scores, suggesting that this easily obtained parameter should be included in future modified HF scores.

Biofortification of Kidney Bean (Phaseolus vulgaris L.) Crops Applying Zinc Sulfate and Ferric Sulfate: Pilot Crop in Colombia.

Agriculture is one of the economic activities with the most potential in Colombia, given its climatic and geographical conditions. Bean cultivation is classified as climbing, which grows in a branched way, and bushy, whose growth occurs up to 70 cm. The objective of this research was to study zinc and iron sulfates in different concentrations as fertilizers capable of increasing the nutritional value of kidney beans (Phaseolus vulgaris L.), whose strategy is known as biofortification, and thus determine the most effective sulfate. The methodology details the sulfate formulations, their preparation, the application of additives, sampling and quantification methods of total iron, total zinc, °Brix, carotenoids, chlorophylls a, b, and antioxidant capacity using the DPPH (2,2-diphenyl-1-picrylhydrazyl) method in leaves and pods. As for the results, it was found that biofortification with iron sulfate and zinc sulfate is a strategy that favors the country's economy and human health, because it allows the increase of minerals, antioxidant capacity and total soluble solids.

The first evidence of hepatitis A virus subgenotype IIIA in the Eastern Brazilian Amazon, 1982-1983.

Hepatitis A virus (HAV) is a major causative agent of acute hepatitis worldwide. Although discovered in 1973, due to limitations of applicable serological and/or molecular methods, HAV remained under limited diagnosis until the late 1980s. This study aimed to retrospectively evaluate the serological and molecular prevalence of the HAV infection among 421 (n = 421) patients with a clinical and laboratory suspicion of acute hepatitis who were admitted in a reference laboratory in the Brazilian Eastern Amazon during 1982 and 1983. The 421 serum samples were screened for anti-HAV IgM antibodies by enzymatic immunoassays. Positive samples were submitted to total RNA purification and tested by Nested reverse-transcription polymerase chain reaction to amplify the HAV-RNA VP1-2A (522 bp) region. Anti-HAV IgM antibodies were detected in 66% (278/421) of the patients. The highest prevalence was observed among males (57.9%, 161/278), and most often among children under 10 years old (63.3%, 176/278). HAV-RNA was detected in 74.4% (207/278) of anti-HAV IgM positive samples. HAV genotyping was performed in 71 samples, and 69 were classified into subgenotype IA. Two samples belonged to the HAV subgenotype IIIA. In this sense, retrospective studies can help in understanding the evolution and determination of wild genotypes and subtypes of HAV.

Immunoglobulin G4-related constrictive pericarditis and the importance of a thorough workup: a case report.

BACKGROUND: Constrictive pericarditis remains a problematic diagnosis and a thorough investigation is critical. Among possible aetiologies, immunoglobulin-G4 (IgG4)-related pericardial disease is an unusual cause of pericardial constriction. We report a challenging diagnostic case of pericardial constriction due to IgG4-related disease. CASE PRESENTATION: A 68-year old male with a history of inferior myocardial infarction with right ventricle (RV) involvement was thrice-hospitalized due to marked ascites and peripheral oedema. Systemic congestion was initially attributed to RV dysfunction due to previous infarction. Yet, at the final admission, a re-assessment echocardiogram followed by cardiac computed tomography, magnetic resonance and right heart catheterization raised a possible diagnosis of constrictive pericarditis with a finding of abnormal pulmonary venous return. Patient therefore underwent pericardiectomy and surgical correction of pulmonary venous return. Pericardium histology revealed an IgG4-related pericardial constriction. Patient was later discharged on corticosteroids with marked symptomatic improvement. CONCLUSION: IgG4-related disease remains a rare cause of pericardium constriction while also presenting a challenging diagnosis in everyday clinical practice. This case exemplifies the difficulties faced by clinicians when reviewing a possible case of constrictive pericarditis, while highlighting the importance of a multimodality assessment.

Pectoralis major muscle quantification by cardiac MRI is a strong predictor of major events in HF.

Clinical overt cardiac cachexia is a late ominous sign in patients with heart failure (HF) and reduced left ventricular ejection fraction (LVEF). The main goal of this study was to assess the feasibility and prognostic significance of muscle mass quantification by cardiac magnetic resonance (CMR) in HF with reduced LVEF. HF patients with LVEF < 40% (HFrEF) referred for CMR were retrospectively identified in a single center. Key exclusion criteria were primary muscle disease, known infiltrative myocardial disease and intracardiac devices. Pectoralis major muscles were measured on standard axial images at the level of the 3rd rib anteriorly. Time to all-cause death or HF hospitalization was the primary endpoint. A total of 298 HF patients were included (mean age 64 ± 12 years; 76% male; mean LVEF 30 ± 8%). During a median follow-up of 22 months (IQR: 12-33), 67 (22.5%) patients met the primary endpoint (33 died and 45 had at least 1 HF hospitalization). In multivariate analysis, LVEF [Hazard Ratio (HR): 0.950; 95% Confidence Interval (CI): 0.917-0.983; p = 0.003), NYHA class I-II vs III-IV (HR: 0.480; CI: 0.272-0.842; p = 0.010), creatinine (HR: 2.653; CI: 1.548-4.545; p < 0.001) and pectoralis major area (HR: 0.873; 95% CI: 0.821-0.929; p < 0.001) were independent predictors of the primary endpoint, when adjusted for gender and NT-pro-BNP levels. Pectoralis major size measured by CMR in HFrEF was independently associated with a higher risk of death or HF hospitalization. Further studies to establish appropriate age and gender-adjusted cut-offs of muscle areas are needed to identify high-risk subgroups.

Genotype-by-environment interactions for reproduction, body composition, and growth traits in maternal-line pigs based on single-step genomic reaction norms.

BACKGROUND: There is an increasing need to account for genotype-by-environment (G × E) interactions in livestock breeding programs to improve productivity and animal welfare across environmental and management conditions. This is even more relevant for pigs because selection occurs in high-health nucleus farms, while commercial pigs are raised in more challenging environments. In this study, we used single-step homoscedastic and heteroscedastic genomic reaction norm models (RNM) to evaluate G × E interactions in Large White pigs, including 8686 genotyped animals, for reproduction (total number of piglets born, TNB; total number of piglets born alive, NBA; total number of piglets weaned, NW), growth (weaning weight, WW; off-test weight, OW), and body composition (ultrasound muscle depth, MD; ultrasound backfat thickness, BF) traits. Genetic parameter estimation and single-step genome-wide association studies (ssGWAS) were performed for each trait. RESULTS: The average performance of contemporary groups (CG) was estimated and used as environmental gradient in the reaction norm analyses. We found that the need to consider heterogeneous residual variance in RNM models was trait dependent. Based on estimates of variance components of the RNM slope and of genetic correlations across environmental gradients, G × E interactions clearly existed for TNB and NBA, existed for WW but were of smaller magnitude, and were not detected for NW, OW, MD, and BF. Based on estimates of the genetic variance explained by the markers in sliding genomic windows in ssGWAS, several genomic regions were associated with the RNM slope for TNB, NBA, and WW, indicating specific biological mechanisms underlying environmental sensitivity, and dozens of novel candidate genes were identified. Our results also provided strong evidence that the X chromosome contributed to the intercept and slope of RNM for litter size traits in pigs. CONCLUSIONS: We provide a comprehensive description of G × E interactions in Large White pigs for economically-relevant traits and identified important genomic regions and candidate genes associated with GxE interactions on several autosomes and the X chromosome. Implementation of these findings will contribute to more accurate genomic estimates of breeding values by considering G × E interactions, in order to genetically improve the environmental robustness of maternal-line pigs.

The amount of late gadolinium enhancement outperforms current guideline-recommended criteria in the identification of patients with hypertrophic cardiomyopathy at risk of sudden cardiac death.

BACKGROUND: Identifying the patients with hypertrophic cardiomyopathy (HCM) in whom the risk of sudden cardiac death (SCD) justifies the implantation of a cardioverter-defibrillator (ICD) in primary prevention remains challenging. Different risk stratification and criteria are used by the European and American guidelines in this setting. We sought to evaluate the role of cardiovascular magnetic resonance (CMR) late gadolinium enhancement (LGE) in improving these risk stratification strategies. METHODS: We conducted a multicentric retrospective analysis of HCM patients who underwent CMR for diagnostic confirmation and/or risk stratification. Eligibility for ICD was assessed according to the HCM Risk-SCD score and the American College of Cardiology Foundation/American Heart Association (ACCF/AHA) algorithm. The amount of LGE was quantified (LGE%) and categorized as 0%, 0.1-10%, 10.1-19.9% and ≥ 20%. The primary endpoint was a composite of SCD, aborted SCD, sustained ventricular tachycardia (VT), or appropriate ICD discharge. RESULTS: A total of 493 patients were available for analysis (58% male, median age 46 years). LGE was present in 79% of patients, with a median LGE% of 2.9% (IQR 0.4-8.4%). The concordance between risk assessment by the HCM Risk-SCD, ACCF/AHA and LGE was relatively weak. During a median follow-up of 3.4 years (IQR 1.5-6.8 years), 23 patients experienced an event (12 SCDs, 6 appropriate ICD discharges and 5 sustained VTs). The amount of LGE was the only independent predictor of outcome (adjusted HR: 1.08; 95% CI: 1.04-1.12; p <  0.001) after adjustment for the HCM Risk-SCD and ACCF/AHA criteria. The amount of LGE showed greater discriminative power (C-statistic 0.84; 95% CI: 0.76-0.91) than the ACCF/AHA (C-statistic 0.61; 95% CI: 0.49-0.72; p for comparison < 0.001) and the HCM Risk-SCD (C-statistic 0.68; 95% CI: 0.59-0.78; p for comparison = 0.006). LGE was able to increase the discriminative power of the ACCF/AHA and HCM Risk-SCD criteria, with net reclassification improvements of 0.36 (p = 0.021) and 0.43 (p = 0.011), respectively. CONCLUSIONS: The amount of LGE seems to outperform the HCM Risk-SCD score and the ACCF/AHA algorithm in the identification of HCM patients at increased risk of SCD and reclassifies a relevant proportion of patients.